Instructions to use Howard881010/heat_transfer_sft_5000_mcq_1epoch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Howard881010/heat_transfer_sft_5000_mcq_1epoch with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-Nemo-Instruct-2407") model = PeftModel.from_pretrained(base_model, "Howard881010/heat_transfer_sft_5000_mcq_1epoch") - Notebooks
- Google Colab
- Kaggle
| base_model: mistralai/Mistral-Nemo-Instruct-2407 | |
| library_name: peft | |
| license: other | |
| tags: | |
| - llama-factory | |
| - lora | |
| - generated_from_trainer | |
| model-index: | |
| - name: heat_transfer_sft_5000_mcq_1epoch | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # heat_transfer_sft_5000_mcq_1epoch | |
| This model is a fine-tuned version of [mistralai/Mistral-Nemo-Instruct-2407](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407) on the heat_transfer_5000_mcq dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.0035 | |
| ## Model description | |
| More information needed | |
| ## Intended uses & limitations | |
| More information needed | |
| ## Training and evaluation data | |
| More information needed | |
| ## Training procedure | |
| ### Training hyperparameters | |
| The following hyperparameters were used during training: | |
| - learning_rate: 0.0001 | |
| - train_batch_size: 10 | |
| - eval_batch_size: 10 | |
| - seed: 42 | |
| - distributed_type: multi-GPU | |
| - num_devices: 4 | |
| - total_train_batch_size: 40 | |
| - total_eval_batch_size: 40 | |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments | |
| - lr_scheduler_type: cosine | |
| - num_epochs: 1 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | | |
| |:-------------:|:------:|:----:|:---------------:| | |
| | 0.004 | 0.2655 | 30 | 0.0038 | | |
| | 0.0037 | 0.5310 | 60 | 0.0036 | | |
| | 0.0035 | 0.7965 | 90 | 0.0035 | | |
| ### Framework versions | |
| - PEFT 0.12.0 | |
| - Transformers 4.46.0 | |
| - Pytorch 2.4.0+cu121 | |
| - Datasets 2.21.0 | |
| - Tokenizers 0.20.1 |